Practitioner Perceptions of Remote Sensing Data and Methodologies

Authors: Scott Stephenson*, University of Connecticut, Colin Gleason, University of Massachusetts Amherst, Luis Alvarez León, Dartmouth College
Topics: Remote Sensing, Political Geography, Applied Geography
Keywords: Remote sensing, property, data, satellite, ethics
Session Type: Paper
Day: 4/7/2019
Start / End Time: 3:55 PM / 5:35 PM
Room: Marshall West, Marriott, Mezzanine Level
Presentation File: No File Uploaded

Remotely sensed data, like all data, have inherent epistemological, social, and political dimensions. Elements such as ownership, specific technologies, strategic priorities, and privileged interpretations influence the availability and applications of remotely sensed data. Yet, remote sensing often enjoys a perception of objectivity and neutrality as a scientific enterprise, highlighting the need for critical examination of the production, use, and appropriation of such data in the public and private sector. In particular, understanding remotely sensed data through a property regime framework reveals the political and economic dimensions that are fundamental to their construction (Alvarez León and Gleason, 2017). Here, we present results from a survey of remote sensing practitioners (scientists, educators and other data users) to provide an empirical basis for the property regime framework in remote sensing applications, and to investigate whether societal concerns about privacy, public and private property, and economic value regarding remotely sensed data are understood and considered by professional users of such data when conducting scientific research. Results concerning participants’ past use of remote sensing data, as well as Likert scale responses indicating practitioner attitudes regarding data access, origin, political neutrality, proliferation, use ethics, and public vs. private ownership are reported. We hope that this study will stimulate a conversation within the scientific research community about the broader societal implications of remote sensing research.

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